Omega-Storage: A Self Organizing Multi-Attribute Storage Technique for Very Large Main Memories.

摘要

Main memory is continuously improving both in price and capacity. With this comes new storage problems as well as new directions of usage. Just before the millennium, several main memory database systems are becoming commercially available. The hot areas include boosting the performance of web-enabled systems, such as search-engines and auctioning systems. We present a novel data storage structure-the omega-storage structure, a high performance data structure, allowing automatically indexed storage of very large amounts of multi-attribute data. The experiments show excellent performance for point retrieval, and highly efficient pruning for pattern searches. It provides the balanced storage previously achieved by random kd-trees, but avoids their increased pattern match search times, by an effective assignment bits of attributes. Moreover, it avoids the sensitivity of the kd-tree to insert orders.